Hierarchical Cluster Analysis Dendrogram Research Articles

Discrimination of wood species based on a carbon nanotube/polymer composite chemiresistor array

AbstractFast and efficient alternative methods for wood species identification are needed to combat illegal logging and to control fair trade. One of the possibilities of rapid wood recognition is via chemiresistor gas sensor arrays (“electronic nose”), the application of which is described in the present paper. Carbon nanotube composites (CNTs) of eight insulating polymers were prepared through solution processing and spin casting. The optimum amount of CNTs in the composites was determined by resistance measurement and the CNTs were characterized by scanning electron microscopy. In the case of static headspace analysis, the sensor responses were reproducible and discernible for the wood species. This was demonstrated based on five wood species (Pterocarpus indicus,Acacia auriculiformis,Gmelina arborea,Vitex parvifloraandDiospyros philippinensis). Discrimination of the data was achieved through principal component analysis (PCA) and hierarchical cluster analysis (HCA). PCA score plots and groupings in HCA dendrograms rendered possible the discrimination of these wood species. The potential application of the sensor array approach for wood species identification is high.

FLAVONOID DISTRIBUTION IN FOUR VARIETIES OF Ficus deltoidea (JACK)

We have previously reported the antioxidant and neuroprotective activities of the aqueous extract of four varieties of Ficus deltoidea (Fd) (Moraceae) namely var kunstleri (Fdvk), var angustifolia (Fdva), var deltoidea (Fdvd) and var intermedia (Fdvi). In this study, flavonoid constituents in aqueous leaf and fig extracts of the four varieties were analyzed and characterized using liquid chromatography mass spectrometer quadrupole-time of flight (LCMS-Q-TOF) via hierarchical cluster analysis (HCA) technique. The HCA dendrogram revealed that the abundant flavonoids among the eight samples are epicatechin, quercetin-3-rutinoside, quercetin 5,4'-di-O-beta-D-glucopyranoside, myricetin and naringenin. The study found that the distribution of the flavonoids differed between the four varieties and varied within the plant parts. To date, the flavonoid distribution of the different plant parts of the four varieties has not been documented. A positive correlation was observed between flavonoid constituents present and radical scavenging activities of the aqueous extracts.

Rapid metabolic discrimination betweenZoysia japonicaandZoysia sinicabased on multivariate analysis of FT-IR spectroscopy

This study aims to establish a system for the rapid discrimination of Zoysia species using metabolite fingerprinting of FT-IR spectroscopy combined with multivariate analysis. Whole cell extracts from leaves of 19 identified Zoysia japonica, 6 identified Zoysia sinica, and 38 different unidentified Zoysia species were subjected to Fourier transform infrared spectroscopy (FT-IR). PCA (principle component analysis) and PLS-DA (partial least square discriminant analysis) from FT-IR spectral data successfully divided the 25 identified turf grasses into two groups, representing good agreement with species identification using molecular markers. PC (principal component) loading values show that the region of the FT-IR spectra are important for the discrimination of Zoysia species. A dendrogram based on hierarchical clustering analysis (HCA) from the PCA and PLS-DA data of turf grasses showed that turf grass samples were divided into Zoysia japonica and Zoysia sinica in a species-dependent manner. PCA and PLS-DA from FT-IR spectral data of Zoysia species identified and unidentified by molecular markers successfully divided the 49 turf grasses into Z. japonica and Z. sinica. In particular, PLS-DA and the HCA dendrogram could mostly discriminate the 47 Z. japonica grasses into two groups depending on their origins (mountainous areas and island area). Considering these results, we suggest that FT-IR fingerprinting combined with multivariate analysis could be applied to discriminate between Zoysia species as well as their geographical origins of various Zoysia species.

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography–mass spectrometry (GC–MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds.

The application of hierarchical cluster analysis and non-negative matrix factorization to European atmospheric monitoring site classification

The effective classification of atmospheric monitoring sites within a network allows conclusions from measurements to be extrapolated beyond the confines of the site itself and applied to larger areas or populations. This is especially important for the European EMEP ‘supersites’ because these are relatively few in number yet are subject to much investment in composition monitoring capability. Here, the representativeness of the two UK EMEP supersites, Auchencorth and Harwell, was evaluated using the hierarchical cluster analysis (HCA) of all available EMEP monitoring sites based on measured ozone concentration datasets for the period 1991–2010. A novel feature was to apply non-negative matrix factorization (NMF) to order the sites within the HCA dendrograms according to the relative anthropogenic influence on ozone. The ordered dendrograms enabled UK sites to be placed more precisely in a European context. For 2007–2010, all 19 UK EMEP sites were assigned to two of the site classification clusters, with 17 of the sites grouping closely with each other in each cluster. Auchencorth clustered with the sites characterised by less modification of hemispheric background ozone levels, whilst Harwell grouped with the sites showing a more polluted regime. A similar grouping of sites occurred between 1991 and 2010, with relatively closer clustering of Polluted UK sites compared with Remote UK sites due to the larger, transboundary spatial domain for which the Remote UK sites are representative. This tight clustering of the majority of the other UK ozone monitoring sites with either one of the supersites, shows that UK background ozone conditions are well represented by Auchencorth and Harwell, and gives confidence that more extensive chemical climatologies developed for the two supersites will have wider geographical relevance.

Fingerprint analysis of Hibiscus mutabilis L. leaves based on ultra performance liquid chromatography with photodiode array detector combined with similarity analysis and hierarchical clustering analysis methods

Background:A method for chemical fingerprint analysis of Hibiscus mutabilis L. leaves was developed based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD) combined with similarity analysis (SA) and hierarchical clustering analysis (HCA).Materials and Methods:10 batches of Hibiscus mutabilis L. leaves samples were collected from different regions of China. UPLC-PAD was employed to collect chemical fingerprints of Hibiscus mutabilis L. leaves.Results:The relative standard deviations (RSDs) of the relative retention times (RRT) and relative peak areas (RPA) of 10 characteristic peaks (one of them was identified as rutin) in precision, repeatability and stability test were less than 3%, and the method of fingerprint analysis was validated to be suitable for the Hibiscus mutabilis L. leaves.Conclusions:The chromatographic fingerprints showed abundant diversity of chemical constituents qualitatively in the 10 batches of Hibiscus mutabilis L. leaves samples from different locations by similarity analysis on basis of calculating the correlation coefficients between each two fingerprints. Moreover, the HCA method clustered the samples into four classes, and the HCA dendrogram showed the close or distant relations among the 10 samples, which was consistent to the SA result to some extent.

Detection of onion postharvest diseases by analyses of headspace volatiles using a gas sensor array and GC-MS

Onion postharvest diseases cause significant losses in storage. Volatile sensing by the gas sensor array technology could be used as a promising alternative method to detect onion diseases. Onions were inoculated with Botrytis allii and Burkholderia cepacia, causal pathogen for Botrytis neck rot and sour skin, respectively. In the first phase of this study, 30 onions with equal number of B. allii inoculated and control healthy onions were measured by the gas sensor array from 8 to 11 days after inoculation (dai) and the principal component analysis (PCA) score plot demonstrated that the gas sensor array responded differently to Botrytis neck rot infected onions from those of healthy onions. In the second phase, 30 onions with 10 for each of the three treatments (Botrytis neck rot, sour skin, control) were measured by the gas sensor array on 5, 6, and 7 dai. The PCA score plot illustrated that three treatments formed three distinct clusters, while a hierarchical cluster analysis dendrogram indicated that the response of the gas sensor array to Botrytis neck rot and sour skin were similar. The correct classification rate of the linear discriminant model for three treatments was over 97.8%. Results from GC-MS showed that total 24 major volatiles were identified from the headspace of three treatments. Sixteen compounds were uniquely present in B. allii and B. cepacia inoculated onion bulbs. Total amount of volatile compounds detected in pathogen inoculated bulbs was one to two orders of magnitude higher than that of control healthy bulbs. This study demonstrated the feasibility of using a gas sensor array to detect two onion postharvest diseases in storage.

Principal component analysis and hierarchical cluster analysis for homogeneity evaluation during the preparation of a wheat flour laboratory reference material for inorganic analysis

Abstract The development of a homogeneity study during the preparation of a wheat flour laboratory reference material (LRM) for use in the quantification of metals and metalloids is reported. Inductively coupled plasma optical emission spectrometry (ICP OES) was used with validation performed using a certified reference material of wheat flour furnished by the National Institute of Standards and Technology (NIST). Copper, iron, manganese, phosphor, strontium and zinc were studied in a within-bottle homogeneity test whereas barium, copper, iron, zinc, manganese, strontium, phosphor and calcium were included in a between batch homogeneity study. Standard univariate analysis of variance (ANOVA) was performed for all analytes. Furthermore an alternative multivariate analysis for homogeneity is proposed by performing ANOVA of principal component scores and by inspection of principal component score graphs and hierarchical cluster analysis dendrograms. The ANOVA F -tests performed on both, the univariate and multivariate parameters, were not significant at the 95% confidence level and indicated homogeneous wheat flour samples. A 10 kg amount of material was processed, which was distributed in 100 bottles, each containing 100 g. For the between-bottle homogeneity test, three replicates were taken from each of 10 bottles selected of the 100 bottles obtained. The results were evaluated using an F-test , which demonstrated no significant difference for the between-bottle results. It is indicative that this material is homogeneous. Afterwards, the influence of the sample mass on the homogeneity of the material was also evaluated by quantification of the elements for 100, 300, 500, 700 and 1000 mg sample masses with all the experiments being performed in triplicate. The F -test was also used for evaluation of these results and demonstrated that the material is homogeneous for masses taken in the 100 to 1000 mg range. All these results were further evaluated employing the principal component analysis (PCA) and hierarchical cluster analysis (HCA) multivariate techniques. Both techniques also demonstrated that the material is perfectly homogeneous for use as laboratory reference material.

Effects of roasting time and storage time on sensory attributes and consumer acceptability of peanut butter in southern Africa

AbstractBy Keith Tomlins, Tunga Rukuni, Angeline Mutungamiri, Sheila Mandeya & Anthony SwetmanThe above article (DOI:10.1002/ts.210) was published online on 9th July 2008 in Wiley Interscience www.interscience.wiley.co.uk. An error was subsequently identified in the article.Page 8, Figure 3 Text – now includes the x‐axis ConsumerPage 8, Figure 3 – amendment to the figure legend as followsFigure 3. Agglomerative hierarchical cluster analysis dendrogram for segmenting consumers (n = 103) into groups of similar perceptions of peanut butters prepared from the Valencia variety roasted for differing times. Dashed line denotes level of dissimilarity along which the four segments (clusters) were selected; x‐axis is not annotated because the number of labels was too high to be legible.The print publication will incorporate the amendments identified by this erratum notice

Heavy metal contents and the water quality of Karasu Creek in Nigde, Turkey

Different sources of pollution in Karasu Creek were investigated to obtain the water quality and ratio of contamination in this region. To achieve the main objectives of the present study, water samples were collected from Karasu Creek, starting from flow pattern at the upstream site of Akkaya Dam to the end of the dam, crossing the place where the Creek drains into. Dissolved oxygen, electrical conductivity, temperature and maximum/minimum pH were measured systematically for 12 months in the stations, where the water samples were collected. Chemical analyses of the water samples were carried out by using Cadas 50 S brand UV spectrometer to find out the Pb, Fe, Cu, Zn, Ni, Cr, Cd, S, F and Cn concentrations. These concentration were determined in microg/lt as 80-850; 180-4,920; 10-6,100; 440-25,530; 130-2,400; 120-280; 20-150; 214,250-1,113,580; 1,560-4,270 and 40-690, respectively. To determine metal levels of the water samples, multivariate analyses (element coefficient correlation, coefficient correlation dendrogram, hierarchical cluster analysis dendrogram, model summary and ANOVA) were used. The analyses yielded highly accurate results. There were positive correlations between some elements and their possible sources were the same. The stations which resembled each other along the creek were divided into three groups. The water quality of the creek was low and had toxic qualities. Eutrophication developed in Akkaya Dam along the creek. The source of pollution was thought to be industrial and residential wastes. Absolute (0-100 m), short distance (100-500 m) and medium distance (500-2,000 m) conservation areas should be determined in pollution areas along Karasu Creek and they should be improved.

Colorimetric Sensor Array for Soft Drink Analysis

Fourteen commercial soft drinks have been analyzed using colorimetric sensor arrays made from a set of 25 chemically responsive dyes printed on a hydrophobic membrane. Digital imaging of the dye array before and after immersion provides a color change profile as a unique fingerprint for each specific analyte. The digital data library generated was analyzed with statistical and chemometric methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). Facile identification of all of the soft drinks was readily achieved using comparison of the color change profiles or a PCA score plot. Using a HCA dendrogram, the misclassification rate was <2%, and even very similar sodas were easily differentiated. In addition, the monitoring of soft drinks as they degas or upon dilution also proved to be possible. This work demonstrates the potential of our colorimetric sensor array technology for quality assurance/control applications of sodas and perhaps other beverages as well.

Assessment of Band-Based Similarity Coefficients for Automatic Type and Subtype Classification of Microbial Isolates Analyzed by Pulsed-Field Gel Electrophoresis

Pulsed-field gel electrophoresis (PFGE) has been the typing method of choice for strain identification in epidemiological studies of several bacterial species of medical importance. The usual procedure for the comparison of strains and assignment of strain type and subtype relies on visual assessment of band difference number, followed by an incremental assignment to the group hosting the most similar type previously seen. Band-based similarity coefficients, such as the Dice or the Jaccard coefficient, are then used for dendrogram construction, which provides a quantitative assessment of strain similarity. PFGE type assignment is based on the definition of a threshold linkage value, below which strains are assigned to the same group. This is typically performed empirically by inspecting the hierarchical cluster analysis dendrogram containing the strains of interest. This approach has the problem that the threshold value selected is dependent on the linkage method used for dendrogram construction. Furthermore, the use of a linkage method skews the original similarity values between strains. In this paper we assess the goodness of classification of several band-based similarity coefficients by comparing it with the band difference number for PFGE type and subtype classification using receiver operating characteristic curves. The procedure described was applied to a collection of PFGE results for 1,798 isolates of Streptococcus pneumoniae, which documented 96 types and 396 subtypes. The band-based similarity coefficients were found to perform equally well for type classification, but with different proportions of false-positive and false-negative classifications in their minimal false discovery rate when they were used for subtype classification.

Visualizing non-hierarchical and hierarchical cluster analyses with clustergrams

In hierarchical cluster analysis dendrogram graphs are used to visualize how clusters are formed. Because each observation is displayed dendrograms are impractical when the data set is large. For non-hierarchical cluster algorithms (e.g. Kmeans) a graph like the dendrogram does not exist. This paper discusses a graph named “clustergram” to examine how cluster members are assigned to clusters as the number of clusters increases. The clustergram can also give insight into algorithms. For example, it can easily be seen that the “single linkage” algorithm tends to form clusters that consist of just one observation. It is also useful in distinguishing between random and deterministic implementations of the Kmeans algorithm. A data set related to asbestos claims and the Thailand Landmine Data are used throughout to illustrate the clustergram.

MORPHOLOGICAL AND CHEMICAL EVALUATION ON HYPERICUM PERFORATUM AND H. MACULATUM IN LITHUANIA

MORPHOLOGICAL AND CHEMICAL EVALUATION ON HYPERICUM PERFORATUM AND H. MACULATUM IN LITHUANIA